中文摘要：

Recent years have witnessed the emergence of image decomposition techniques which effectively separate an image into a piecewise smooth base layer and several residual detail layers. However, the intricacy of detail patterns in some cases may result in side-effects including remnant textures, wronglysmoothed edges, and distorted appearance. We introduce a new way to construct an edge-preserving image decomposition with properties of detail smoothing, edge retention, and shape fitting. Our method has three main steps: suppressing highcontrast details via a windowed variation similarity measure, detecting salient edges to produce an edgeguided image, and fitting the original shape using a weighted least squares framework. Experimental results indicate that the proposed approach can appropriately smooth non-edge regions even when textures and structures are similar in scale. The effectiveness of our approach is demonstrated in the contexts of detail manipulation, HDR tone mapping,and image abstraction.